Research on the Impact of Regular Exercise Behavior of College Students on Academic Stress and Sleep Quality during the COVID-19 Pandemic.

When college students face the COVID-19 pandemic and new learning challenges simultaneously, how to reduce or alleviate their own academic stress has become a topic of concern to students and their parents. The psychological and physiological benefits of regular exercise have been confirmed by related studies. This study aimed to explore the impact of college students' regular exercise behavior on academic stress and sleep quality during the COVID-19 pandemic. This study used a purposive sampling method to collect data through online questionnaires posted to relevant college student groups in northern, central, southern, and eastern Taiwan and the outlying islands. A total of 320 questionnaires were collected, with a response rate of 91.4%; based on 304 valid questionnaires. The validity rate was 95%. The obtained data were entered in SPSS 24.0 statistical software, and the correlation between variables was analyzed with AMOS 24.0 statistical software. The results show that hypothesis 1 is established, that is, regular exercise behavior of college students during the COVID-19 pandemic has a significant negative impact on academic stress, meaning that during the COVID-19 pandemic, if college students can use their spare time to make exercise part of their life, such a regular schedule will help reduce their academic stress. In addition, the empirical results show that hypothesis 2 is established, that is, regular exercise behavior of college students during the COVID-19 pandemic has a significant positive impact on sleep quality. A possible reason is that under the COVID-19 pandemic, the efficiency of the body to absorb oxygen is increased through regular exercise, which reduces pressure and improves sleep quality. Hypothesis 3 is also confirmed, that is, the academic stress of college students during the COVID-19 pandemic has a significant negative impact on sleep quality. The reason may be that many leisure and social activities have been suspended during the COVID-19 pandemic, and thus college students exercised and studied during the time they originally intended for leisure and social activities, which reduced their academic stress, stabilized their mood, and improved their sleep quality.

An artificial intelligence system to predict the optimal timing for mechanical ventilation weaning for intensive care unit patients: A two-stage prediction approach

Background For the intensivists, accurate assessment of the ideal timing for successful weaning from the mechanical ventilation (MV) in the intensive care unit (ICU) is very challenging. Purpose Using artificial intelligence (AI) approach to build two-stage predictive models, namely, the try-weaning stage and weaning MV stage to determine the optimal timing of weaning from MV for ICU intubated patients, and implement into practice for assisting clinical decision making. Methods AI and machine learning (ML) technologies were used to establish the predictive models in the stages. Each stage comprised 11 prediction time points with 11 prediction models. Twenty-five features were used for the first-stage models while 20 features were used for the second-stage models. The optimal models for each time point were selected for further practical implementation in a digital dashboard style. Seven machine learning algorithms including Logistic Regression (LR), Random Forest (RF), Support Vector Machines (SVM), K Nearest Neighbor (KNN), lightGBM, XGBoost, and Multilayer Perception (MLP) were used. The electronic medical records of the intubated ICU patients of Chi Mei Medical Center (CMMC) from 2016 to 2019 were included for modeling. Models with the highest area under the receiver operating characteristic curve (AUC) were regarded as optimal models and used to develop the prediction system accordingly. Results A total of 5,873 cases were included in machine learning modeling for Stage 1 with the AUCs of optimal models ranging from 0.843 to 0.953. Further, 4,172 cases were included for Stage 2 with the AUCs of optimal models ranging from 0.889 to 0.944. A prediction system (dashboard) with the optimal models of the two stages was developed and deployed in the ICU setting. Respiratory care members expressed high recognition of the AI dashboard assisting ventilator weaning decisions. Also, the impact analysis of with- and without-AI assistance revealed that our AI models could shorten the patients’ intubation time by 21 hours, besides gaining the benefit of substantial consistency between these two decision-making strategies. Conclusion We noticed that the two-stage AI prediction models could effectively and precisely predict the optimal timing to wean intubated patients in the ICU from ventilator use. This could reduce patient discomfort, improve medical quality, and lower medical costs. This AI-assisted prediction system is beneficial for clinicians to cope with a high demand for ventilators during the COVID-19 pandemic.

How to improve the problem of hotel manpower shortage in the COVID-19 epidemic environment? Exploring the effectiveness of the hotel practice training system.

This study aimed to examine the role of effective employee training in the sustainable growth and corporate social responsibility of hotels during the postpandemic period. An initial respondent pool was selected using purposive sampling, and 280 questionnaires were finally obtained by snowball sampling from September 2019 to February 2020. The sample was analyzed using basic statistical tests, the Pearson correlation coefficient, and multivariate regression. We then interpreted the sample data through consultation with scholars and practitioners in hotel management. Finally, the data were analyzed using multivariate verification. The results indicated that China Binhai Hotel could not foster consistent employee enthusiasm and fulfill its corporate social responsibilities during the postpandemic period due to deficiencies in its human resources training, employee benefit, job rotation, and incentive systems. We suggest for hotels to promote corporate culture, improve the system of promotion, increase employee benefits, and adjust the workplace environment and equipment provided to employees. These will improve employee attitudes toward hotel management, improve work efficiency, increase retention, and solve the problem of personnel shortage during the postpandemic period.

The Behavioral Intention and Influencing Factors of Medical Staff toward COVID-19 Vaccinations.

This study mainly explored the behavioral intention and influencing factors of medical staff toward COVID-19 vaccinations. Medical staff were taken as the research subjects. This study selected 300 research subjects by the intentional sampling method and conducted a questionnaire survey. A total of 260 questionnaires were recovered (a recovery rate of 86%), and the number of valid questionnaires was 212, for an effective questionnaire rate of 81%. SPSS and AMOS were used for statistical analysis. As known from the research results: (1) medical staffs' perception of COVID-19 vaccinations had a positive and significant impact on their behavioral intention for receiving COVID-19 vaccinations; (2) medical staffs' perception of COVID-19 vaccinations had a negative and significant impact on the barriers to receiving COVID-19 vaccinations; (3) medical staffs' motivation of receiving COVID-19 vaccinations had a positive and significant positive effect on their behavioral intention of receiving COVID-19 vaccinations; and (4) medical staffs' motivation of receiving COVID-19 vaccinations had a positive and significant impact on the barrier to receiving COVID-19 vaccinations.

The Behavioral Intention and Influencing Factors of Medical Staff toward COVID-19 Vaccinations

This study mainly explored the behavioral intention and influencing factors of medical staff toward COVID-19 vaccinations. Medical staff were taken as the research subjects. This study selected 300 research subjects by the intentional sampling method and conducted a questionnaire survey. A total of 260 questionnaires were recovered (a recovery rate of 86%), and the number of valid questionnaires was 212, for an effective questionnaire rate of 81%. SPSS and AMOS were used for statistical analysis. As known from the research results: (1) medical staffs' perception of COVID-19 vaccinations had a positive and significant impact on their behavioral intention for receiving COVID-19 vaccinations;(2) medical staffs' perception of COVID-19 vaccinations had a negative and significant impact on the barriers to receiving COVID-19 vaccinations;(3) medical staffs' motivation of receiving COVID-19 vaccinations had a positive and significant positive effect on their behavioral intention of receiving COVID-19 vaccinations;and (4) medical staffs' motivation of receiving COVID-19 vaccinations had a positive and significant impact on the barrier to receiving COVID-19 vaccinations.

Effects of Leisure Obstacles, Job Satisfaction, and Physical and Mental Health on Job Intentions of Medical Workers Exposed to COVID-19 Infection Risk and Workplace Stress.

The purpose of this study was to investigate the effects of leisure obstacles, job satisfaction, physical and mental health, and work intentions of medical workers in Taiwan. SPSS 26.0 and AMOS 24.0 statistical software were used to analyze 208 questionnaires by basic statistical tests, t-tests, and structural model analysis. Results: Under the epidemic, medical workers were unable to develop job identity due to low promotion opportunities and low job achievement. The lack of recreational exercise skills, time, and information created leisure obstacles. In addition, they were unable to express their true selves freely at work, which led to health problems such as reduced enthusiasm, mental weakness, and emotional irritability. In particular, female medical workers felt more strongly about the issues of leisure obstacles and the intention to stay in their jobs. The study found that the higher their job satisfaction, the higher their intention to stay in the job, while the more pronounced the leisure obstacles and physical and mental health problems, the more pronounced their intention to leave.